A Akbarzadeh Bagheban, E Maserat, M Hemmati,
Volume 3, Issue 1 (21 2007)
Abstract
Background & Objectives: There is little doubt about the importance of accurate statistics and reliable information in the promoting community health and optimizing health care. Therefore, the existence of a correct, accurate and up to date database is an absolute necessity. Accurate identification of the cause in death certificates can make an invaluable contribution to the development of such a database. The purpose of this research was to assess the current defects and shortcomings in death certificates and to evaluate the degree of agreement between the diagnoses recorded in hospital files those figuring on death certificates.
Methods: This was an analytic cross-sectional study. In this survey of 659 medical records of dead patients in Loghman Hospital, during 2005, 290 medical records were selected using a systematic sampling method. The selection of these records were based on record numbers in the archives and involved the extraction of the following data: the physician's field of specialty, the patient's identity, code for the main diagnosis, the code for the external cause on the admission form, and the code for the cause of death on the death (as defined in ICD-10) was recorded. The agreement between primary and final diagnoses and also the agreement between final diagnosis and the cause of death were assessed in relation with the physician's specialty using Fisher's Exact Test. Overall agreement between different diagnoses was measured using the kappa statistic.
Results: The degree of agreement between primary and final diagnosis was very good (k = 0.83) and agreement between final diagnosis and cause of death was excellent (k = 0.95). Fisher's exact test showed that agreement between primary and final diagnoses and between final diagnoses and cause of death doesn't depend on the physician's specialty (in both cases p>0.01). In 62% percent of the cases death had occurred without interference from an external cause. Among the 38% in which there was an external cause, 21% involved poisoning with suicidal intent, 12% were due to accidental poisoning, 4% were motor accidents, and 1% were due to other reasons.
Conclusions: There was a high degree of agreement between different diagnoses in some specialties, while didn't observe such agreement in other specialties. Since accurate diagnosis helps in identifying the cause of death and death information is an important indicator of health at community level, we recommend that physicians pay greater attention to accurate recording of the cause of death. This will make it possible to draw meaningful comparisons between the causes of death in Iran and those in other countries.
Ha Nikbakht, H Ghaem, Hr Tabatabaee, A Mirahmadizadeh, S Hassanipour, S Zahmatkesh, A Hemmati, F Moradi, A Abbasi,
Volume 15, Issue 3 (Vol.15, No.3 2019)
Abstract
Background and Objectives: Anthropometric indices, especially weight, provide useful information for the care and treatment of newborn infants and can be used to identify infants at risk. Therefore, this study was conducted to examine the mean weight, height and head circumference measurements of infants and some related factors.
Methods: This cross-sectional study was performed to investigate the anthropometric indices (weight, height and head circumference), demographic characteristics, and delivery data of 1484 newborns in 2016 using multi-stage sampling. Moreover, the predictors of these indices were analyzed using a linear regression model.
Results: The mean weight, height and head circumference of the newborn infants was 3185 ± 465 g, 49.92 ± 2.92 cm, and 34.58 ± 2.29 cm respectively, and 7% of newborns were low birth weight. The male newborns weighed 57.29 g more than females on average at birth (p <0.05). Besides, the height and head circumference of the male newborns were 0.15 and 0.10 cm larger than the female newborns respectively but the difference was not statistically significant. In addition to gender, gestational age at birth (week) and type of delivery correlated with all three anthropometric indices in multivariate analysis.
Conclusion: Identifying and controlling largely adjustable risk factors can make it possible to prevent low anthropometric parameters, particularly low birth weight.
